1. Spring Batch Integration

1.1. Spring Batch Integration Introduction

Many users of Spring Batch may encounter requirements that are outside the scope of Spring Batch but that may be efficiently and concisely implemented by using Spring Integration. Conversely, Spring Integration users may encounter Spring Batch requirements and need a way to efficiently integrate both frameworks. In this context, several patterns and use-cases emerge, and Spring Batch Integration addresses those requirements.

The line between Spring Batch and Spring Integration is not always clear, but two pieces of advice can help: Think about granularity, and apply common patterns. Some of those common patterns are described in this reference manual section.

Adding messaging to a batch process enables automation of operations and also separation and strategizing of key concerns. For example, a message might trigger a job to execute, and then the sending of the message can be exposed in a variety of ways. Alternatively, when a job completes or fails, that event might trigger a message to be sent, and the consumers of those messages might have operational concerns that have nothing to do with the application itself. Messaging can also be embedded in a job (for example reading or writing items for processing via channels). Remote partitioning and remote chunking provide methods to distribute workloads over a number of workers.

This section covers the following key concepts:

1.1.1. Namespace Support

Since Spring Batch Integration 1.3, dedicated XML Namespace support was added, with the aim to provide an easier configuration experience. In order to activate the namespace, add the following namespace declarations to your Spring XML Application Context file:

<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:batch-int="http://www.springframework.org/schema/batch-integration"
  xsi:schemaLocation="
    http://www.springframework.org/schema/batch-integration
    https://www.springframework.org/schema/batch-integration/spring-batch-integration.xsd">

    ...

</beans>

A fully configured Spring XML Application Context file for Spring Batch Integration may look like the following:

<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:int="http://www.springframework.org/schema/integration"
  xmlns:batch="http://www.springframework.org/schema/batch"
  xmlns:batch-int="http://www.springframework.org/schema/batch-integration"
  xsi:schemaLocation="
    http://www.springframework.org/schema/batch-integration
    https://www.springframework.org/schema/batch-integration/spring-batch-integration.xsd
    http://www.springframework.org/schema/batch
    https://www.springframework.org/schema/batch/spring-batch.xsd
    http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/integration
    https://www.springframework.org/schema/integration/spring-integration.xsd">

    ...

</beans>

Appending version numbers to the referenced XSD file is also allowed, but, as a version-less declaration always uses the latest schema, we generally do not recommend appending the version number to the XSD name. Adding a version number could possibly create issues when updating the Spring Batch Integration dependencies, as they may require more recent versions of the XML schema.

1.1.2. Launching Batch Jobs through Messages

When starting batch jobs by using the core Spring Batch API, you basically have 2 options:

  • From the command line, with the CommandLineJobRunner

  • Programmatically, with either JobOperator.start() or JobLauncher.run()

For example, you may want to use the CommandLineJobRunner when invoking Batch Jobs by using a shell script. Alternatively, you may use the JobOperator directly (for example, when using Spring Batch as part of a web application). However, what about more complex use cases? Maybe you need to poll a remote (S)FTP server to retrieve the data for the Batch Job or your application has to support multiple different data sources simultaneously. For example, you may receive data files not only from the web, but also from FTP and other sources. Maybe additional transformation of the input files is needed before invoking Spring Batch.

Therefore, it would be much more powerful to execute the batch job using Spring Integration and its numerous adapters. For example, you can use a File Inbound Channel Adapter to monitor a directory in the file-system and start the Batch Job as soon as the input file arrives. Additionally, you can create Spring Integration flows that use multiple different adapters to easily ingest data for your batch jobs from multiple sources simultaneously using only configuration. Implementing all these scenarios with Spring Integration is easy, as it allows for decoupled, event-driven execution of the JobLauncher .

Spring Batch Integration provides the JobLaunchingMessageHandler class that you can use to launch batch jobs. The input for the JobLaunchingMessageHandler is provided by a Spring Integration message, which has a payload of type JobLaunchRequest . This class is a wrapper around the Job that needs to be launched and around the JobParameters necessary to launch the Batch job.

The following image illustrates the typical Spring Integration message flow in order to start a Batch job. The EIP (Enterprise Integration Patterns) website provides a full overview of messaging icons and their descriptions.

Launch Batch Job

Figure 1. Launch Batch Job

Transforming a file into a JobLaunchRequest
package io.spring.sbi;

import org.springframework.batch.core.Job;
import org.springframework.batch.core.JobParametersBuilder;
import org.springframework.batch.integration.launch.JobLaunchRequest;
import org.springframework.integration.annotation.Transformer;
import org.springframework.messaging.Message;

import java.io.File;

public class FileMessageToJobRequest {
    private Job job;
    private String fileParameterName;

    public void setFileParameterName(String fileParameterName) {
        this.fileParameterName = fileParameterName;
    }

    public void setJob(Job job) {
        this.job = job;
    }

    @Transformer
    public JobLaunchRequest toRequest(Message<File> message) {
        JobParametersBuilder jobParametersBuilder =
            new JobParametersBuilder();

        jobParametersBuilder.addString(fileParameterName,
            message.getPayload().getAbsolutePath());

        return new JobLaunchRequest(job, jobParametersBuilder.toJobParameters());
    }
}
The JobExecution Response

When a batch job is being executed, a JobExecution instance is returned. This instance can be used to determine the status of an execution. If a JobExecution is able to be created successfully, it is always returned, regardless of whether or not the actual execution is successful.

The exact behavior on how the JobExecution instance is returned depends on the provided TaskExecutor . If a synchronous (single-threaded) TaskExecutor implementation is used, the JobExecution response is returned only after the job completes. When using an asynchronous TaskExecutor , the JobExecution instance is returned immediately. Users can then take the id of JobExecution instance (with JobExecution.getJobId() ) and query the JobRepository for the job’s updated status using the JobExplorer . For more information, please refer to the Spring Batch reference documentation on Querying the Repository.

Spring Batch Integration Configuration

The following configuration creates a file inbound-channel-adapter to listen for CSV files in the provided directory, hand them off to our transformer ( FileMessageToJobRequest ), launch the job via the Job Launching Gateway , and then log the output of the JobExecution with the logging-channel-adapter .

XML Configuration

<int:channel id="inboundFileChannel"/>
<int:channel id="outboundJobRequestChannel"/>
<int:channel id="jobLaunchReplyChannel"/>

<int-file:inbound-channel-adapter id="filePoller"
    channel="inboundFileChannel"
    directory="file:/tmp/myfiles/"
    filename-pattern="*.csv">
  <int:poller fixed-rate="1000"/>
</int-file:inbound-channel-adapter>

<int:transformer input-channel="inboundFileChannel"
    output-channel="outboundJobRequestChannel">
  <bean class="io.spring.sbi.FileMessageToJobRequest">
    <property name="job" ref="personJob"/>
    <property name="fileParameterName" value="input.file.name"/>
  </bean>
</int:transformer>

<batch-int:job-launching-gateway request-channel="outboundJobRequestChannel"
    reply-channel="jobLaunchReplyChannel"/>

<int:logging-channel-adapter channel="jobLaunchReplyChannel"/>

Java Configuration

@Bean
public FileMessageToJobRequest fileMessageToJobRequest() {
    FileMessageToJobRequest fileMessageToJobRequest = new FileMessageToJobRequest();
    fileMessageToJobRequest.setFileParameterName("input.file.name");
    fileMessageToJobRequest.setJob(personJob());
    return fileMessageToJobRequest;
}

@Bean
public JobLaunchingGateway jobLaunchingGateway() {
    SimpleJobLauncher simpleJobLauncher = new SimpleJobLauncher();
    simpleJobLauncher.setJobRepository(jobRepository);
    simpleJobLauncher.setTaskExecutor(new SyncTaskExecutor());
    JobLaunchingGateway jobLaunchingGateway = new JobLaunchingGateway(simpleJobLauncher);

    return jobLaunchingGateway;
}

@Bean
public IntegrationFlow integrationFlow(JobLaunchingGateway jobLaunchingGateway) {
    return IntegrationFlows.from(Files.inboundAdapter(new File("/tmp/myfiles")).
                    filter(new SimplePatternFileListFilter("*.csv")),
            c -> c.poller(Pollers.fixedRate(1000).maxMessagesPerPoll(1))).
            handle(fileMessageToJobRequest()).
            handle(jobLaunchingGateway).
            log(LoggingHandler.Level.WARN, "headers.id + ': ' + payload").
            get();
}
Example ItemReader Configuration

Now that we are polling for files and launching jobs, we need to configure our Spring Batch ItemReader (for example) to use the files found at the location defined by the job parameter called "input.file.name", as shown in the following bean configuration:

XML Configuration

<bean id="itemReader" class="org.springframework.batch.item.file.FlatFileItemReader"
    scope="step">
  <property name="resource" value="file://#{jobParameters['input.file.name']}"/>
    ...
</bean>

Java Configuration

@Bean
@StepScope
public ItemReader sampleReader(@Value("#{jobParameters[input.file.name]}") String resource) {
...
    FlatFileItemReader flatFileItemReader = new FlatFileItemReader();
    flatFileItemReader.setResource(new FileSystemResource(resource));
...
    return flatFileItemReader;
}

The main points of interest in the preceding example are injecting the value of #{jobParameters['input.file.name']} as the Resource property value and setting the ItemReader bean to have Step scope . Setting the bean to have Step scope takes advantage of the late binding support, which allows access to the jobParameters variable.

1.2. Available Attributes of the Job-Launching Gateway

The job-launching gateway has the following attributes that you can set to control a job:

  • id : Identifies the underlying Spring bean definition, which is an instance of either:

  • EventDrivenConsumer

    • PollingConsumer (The exact implementation depends on whether the component’s input channel is a SubscribableChannel or PollableChannel .)
  • auto-startup : Boolean flag to indicate that the endpoint should start automatically on startup. The default is true .

  • request-channel : The input MessageChannel of this endpoint.

  • reply-channel : MessageChannel to which the resulting JobExecution payload is sent.

  • reply-timeout : Lets you specify how long (in milliseconds) this gateway waits for the reply message to be sent successfully to the reply channel before throwing an exception. This attribute only applies when the channel might block (for example, when using a bounded queue channel that is currently full). Also, keep in mind that, when sending to a DirectChannel , the invocation occurs in the sender’s thread. Therefore, the failing of the send operation may be caused by other components further downstream. The reply-timeout attribute maps to the sendTimeout property of the underlying MessagingTemplate instance. If not specified, the attribute defaults to<emphasis>-1</emphasis>, meaning that, by default, the Gateway waits indefinitely.

  • job-launcher : Optional. Accepts a custom JobLauncher bean reference. If not specified the adapter re-uses the instance that is registered under the id of jobLauncher . If no default instance exists, an exception is thrown.

  • order : Specifies the order of invocation when this endpoint is connected as a subscriber to a SubscribableChannel .

1.3. Sub-Elements

When this Gateway is receiving messages from a PollableChannel , you must either provide a global default Poller or provide a Poller sub-element to the Job Launching Gateway , as shown in the following example:

XML Configuration

<batch-int:job-launching-gateway request-channel="queueChannel"
    reply-channel="replyChannel" job-launcher="jobLauncher">
  <int:poller fixed-rate="1000">
</batch-int:job-launching-gateway>

Java Configuration

@Bean
@ServiceActivator(inputChannel = "queueChannel", poller = @Poller(fixedRate="1000"))
public JobLaunchingGateway sampleJobLaunchingGateway() {
    JobLaunchingGateway jobLaunchingGateway = new JobLaunchingGateway(jobLauncher());
    jobLaunchingGateway.setOutputChannel(replyChannel());
    return jobLaunchingGateway;
}

1.3.1. Providing Feedback with Informational Messages

As Spring Batch jobs can run for long times, providing progress information is often critical. For example, stake-holders may want to be notified if some or all parts of a batch job have failed. Spring Batch provides support for this information being gathered through:

  • Active polling

  • Event-driven listeners

When starting a Spring Batch job asynchronously (for example, by using the Job Launching Gateway ), a JobExecution instance is returned. Thus, JobExecution.getJobId() can be used to continuously poll for status updates by retrieving updated instances of the JobExecution from the JobRepository by using the JobExplorer . However, this is considered sub-optimal, and an event-driven approach should be preferred.

Therefore, Spring Batch provides listeners, including the three most commonly used listeners:

  • StepListener

  • ChunkListener

  • JobExecutionListener

In the example shown in the following image, a Spring Batch job has been configured with a StepExecutionListener . Thus, Spring Integration receives and processes any step before or after events. For example, the received StepExecution can be inspected by using a Router . Based on the results of that inspection, various things can occur (such as routing a message to a Mail Outbound Channel Adapter), so that an Email notification can be sent out based on some condition.

Handling Informational Messages

Figure 2. Handling Informational Messages

The following two-part example shows how a listener is configured to send a message to a Gateway for a StepExecution events and log its output to a logging-channel-adapter .

First, create the notification integration beans:

XML Configuration

<int:channel id="stepExecutionsChannel"/>

<int:gateway id="notificationExecutionsListener"
    service-interface="org.springframework.batch.core.StepExecutionListener"
    default-request-channel="stepExecutionsChannel"/>

<int:logging-channel-adapter channel="stepExecutionsChannel"/>

Java Configuration

@Bean
@ServiceActivator(inputChannel = "stepExecutionsChannel")
public LoggingHandler loggingHandler() {
    LoggingHandler adapter = new LoggingHandler(LoggingHandler.Level.WARN);
    adapter.setLoggerName("TEST_LOGGER");
    adapter.setLogExpressionString("headers.id + ': ' + payload");
    return adapter;
}

@MessagingGateway(name = "notificationExecutionsListener", defaultRequestChannel = "stepExecutionsChannel")
public interface NotificationExecutionListener extends StepExecutionListener {}

Note

You will need to add the @IntegrationComponentScan annotation to your configuration.

Second, modify your job to add a step-level listener:

XML Configuration

<job id="importPayments">
    <step id="step1">
        <tasklet ../>
            <chunk ../>
            <listeners>
                <listener ref="notificationExecutionsListener"/>
            </listeners>
        </tasklet>
        ...
    </step>
</job>

Java Configuration

public Job importPaymentsJob() {
    return jobBuilderFactory.get("importPayments")
        .start(stepBuilderFactory.get("step1")
                .chunk(200)
                .listener(notificationExecutionsListener())
                ...
}

1.3.2. Asynchronous Processors

Asynchronous Processors help you to scale the processing of items. In the asynchronous processor use case, an AsyncItemProcessor serves as a dispatcher, executing the logic of the ItemProcessor for an item on a new thread. Once the item completes, the Future is passed to the AsynchItemWriter to be written.

Therefore, you can increase performance by using asynchronous item processing, basically allowing you to implement fork-join scenarios. The AsyncItemWriter gathers the results and writes back the chunk as soon as all the results become available.

The following example shows how to configuration the AsyncItemProcessor :

XML Configuration

<bean id="processor"
    class="org.springframework.batch.integration.async.AsyncItemProcessor">
  <property name="delegate">
    <bean class="your.ItemProcessor"/>
  </property>
  <property name="taskExecutor">
    <bean class="org.springframework.core.task.SimpleAsyncTaskExecutor"/>
  </property>
</bean>

Java Configuration

@Bean
public AsyncItemProcessor processor(ItemProcessor itemProcessor, TaskExecutor taskExecutor) {
    AsyncItemProcessor asyncItemProcessor = new AsyncItemProcessor();
    asyncItemProcessor.setTaskExecutor(taskExecutor);
    asyncItemProcessor.setDelegate(itemProcessor);
    return asyncItemProcessor;
}

The delegate property refers to your ItemProcessor bean, and the taskExecutor property refers to the TaskExecutor of your choice.

The following example shows how to configure the AsyncItemWriter :

XML Configuration

<bean id="itemWriter"
    class="org.springframework.batch.integration.async.AsyncItemWriter">
  <property name="delegate">
    <bean id="itemWriter" class="your.ItemWriter"/>
  </property>
</bean>

Java Configuration

@Bean
public AsyncItemWriter writer(ItemWriter itemWriter) {
    AsyncItemWriter asyncItemWriter = new AsyncItemWriter();
    asyncItemWriter.setDelegate(itemWriter);
    return asyncItemWriter;
}

Again, the delegate property is actually a reference to your ItemWriter bean.

1.3.3. Externalizing Batch Process Execution

The integration approaches discussed so far suggest use cases where Spring Integration wraps Spring Batch like an outer-shell. However, Spring Batch can also use Spring Integration internally. Using this approach, Spring Batch users can delegate the processing of items or even chunks to outside processes. This allows you to offload complex processing. Spring Batch Integration provides dedicated support for:

  • Remote Chunking

  • Remote Partitioning

Remote Chunking

Remote Chunking

Figure 3. Remote Chunking

Taking things one step further, one can also externalize the chunk processing by using the ChunkMessageChannelItemWriter (provided by Spring Batch Integration), which sends items out and collects the result. Once sent, Spring Batch continues the process of reading and grouping items, without waiting for the results. Rather, it is the responsibility of the ChunkMessageChannelItemWriter to gather the results and integrate them back into the Spring Batch process.

With Spring Integration, you have full control over the concurrency of your processes (for instance, by using a QueueChannel instead of a DirectChannel ). Furthermore, by relying on Spring Integration’s rich collection of Channel Adapters (such as JMS and AMQP), you can distribute chunks of a Batch job to external systems for processing.

A simple job with a step to be remotely chunked might have a configuration similar to the following:

XML Configuration

<job id="personJob">
  <step id="step1">
    <tasklet>
      <chunk reader="itemReader" writer="itemWriter" commit-interval="200"/>
    </tasklet>
    ...
  </step>
</job>

Java Configuration

public Job chunkJob() {
     return jobBuilderFactory.get("personJob")
             .start(stepBuilderFactory.get("step1")
                     .<Person, Person>chunk(200)
                     .reader(itemReader())
                     .writer(itemWriter())
                     .build())
             .build();
 }

The ItemReader reference points to the bean you want to use for reading data on the master. The ItemWriter reference points to a special ItemWriter (called ChunkMessageChannelItemWriter ), as described above. The processor (if any) is left off the master configuration, as it is configured on the worker. The following configuration provides a basic master setup. You should check any additional component properties, such as throttle limits and so on, when implementing your use case.

XML Configuration

<bean id="connectionFactory" class="org.apache.activemq.ActiveMQConnectionFactory">
  <property name="brokerURL" value="tcp://localhost:61616"/>
</bean>

<int-jms:outbound-channel-adapter id="jmsRequests" destination-name="requests"/>

<bean id="messagingTemplate"
    class="org.springframework.integration.core.MessagingTemplate">
  <property name="defaultChannel" ref="requests"/>
  <property name="receiveTimeout" value="2000"/>
</bean>

<bean id="itemWriter"
    class="org.springframework.batch.integration.chunk.ChunkMessageChannelItemWriter"
    scope="step">
  <property name="messagingOperations" ref="messagingTemplate"/>
  <property name="replyChannel" ref="replies"/>
</bean>

<int:channel id="replies">
  <int:queue/>
</int:channel>

<int-jms:message-driven-channel-adapter id="jmsReplies"
    destination-name="replies"
    channel="replies"/>

Java Configuration

@Bean
public org.apache.activemq.ActiveMQConnectionFactory connectionFactory() {
    ActiveMQConnectionFactory factory = new ActiveMQConnectionFactory();
    factory.setBrokerURL("tcp://localhost:61616");
    return factory;
}

/*
 * Configure outbound flow (requests going to workers)
 */
@Bean
public DirectChannel requests() {
    return new DirectChannel();
}

@Bean
public IntegrationFlow outboundFlow(ActiveMQConnectionFactory connectionFactory) {
    return IntegrationFlows
            .from(requests())
            .handle(Jms.outboundAdapter(connectionFactory).destination("requests"))
            .get();
}

/*
 * Configure inbound flow (replies coming from workers)
 */
@Bean
public QueueChannel replies() {
    return new QueueChannel();
}

@Bean
public IntegrationFlow inboundFlow(ActiveMQConnectionFactory connectionFactory) {
    return IntegrationFlows
            .from(Jms.messageDrivenChannelAdapter(connectionFactory).destination("replies"))
            .channel(replies())
            .get();
}

/*
 * Configure the ChunkMessageChannelItemWriter
 */
@Bean
public ItemWriter<Integer> itemWriter() {
    MessagingTemplate messagingTemplate = new MessagingTemplate();
    messagingTemplate.setDefaultChannel(requests());
    messagingTemplate.setReceiveTimeout(2000);
    ChunkMessageChannelItemWriter<Integer> chunkMessageChannelItemWriter
            = new ChunkMessageChannelItemWriter<>();
    chunkMessageChannelItemWriter.setMessagingOperations(messagingTemplate);
    chunkMessageChannelItemWriter.setReplyChannel(replies());
    return chunkMessageChannelItemWriter;
}

The preceding configuration provides us with a number of beans. We configure our messaging middleware using ActiveMQ and the inbound/outbound JMS adapters provided by Spring Integration. As shown, our itemWriter bean, which is referenced by our job step, uses the ChunkMessageChannelItemWriter for writing chunks over the configured middleware.

Now we can move on to the worker configuration, as shown in the following example:

XML Configuration

<bean id="connectionFactory" class="org.apache.activemq.ActiveMQConnectionFactory">
  <property name="brokerURL" value="tcp://localhost:61616"/>
</bean>

<int:channel id="requests"/>
<int:channel id="replies"/>

<int-jms:message-driven-channel-adapter id="incomingRequests"
    destination-name="requests"
    channel="requests"/>

<int-jms:outbound-channel-adapter id="outgoingReplies"
    destination-name="replies"
    channel="replies">
</int-jms:outbound-channel-adapter>

<int:service-activator id="serviceActivator"
    input-channel="requests"
    output-channel="replies"
    ref="chunkProcessorChunkHandler"
    method="handleChunk"/>

<bean id="chunkProcessorChunkHandler"
    class="org.springframework.batch.integration.chunk.ChunkProcessorChunkHandler">
  <property name="chunkProcessor">
    <bean class="org.springframework.batch.core.step.item.SimpleChunkProcessor">
      <property name="itemWriter">
        <bean class="io.spring.sbi.PersonItemWriter"/>
      </property>
      <property name="itemProcessor">
        <bean class="io.spring.sbi.PersonItemProcessor"/>
      </property>
    </bean>
  </property>
</bean>

Java Configuration

@Bean
public org.apache.activemq.ActiveMQConnectionFactory connectionFactory() {
    ActiveMQConnectionFactory factory = new ActiveMQConnectionFactory();
    factory.setBrokerURL("tcp://localhost:61616");
    return factory;
}

/*
 * Configure inbound flow (requests coming from the master)
 */
@Bean
public DirectChannel requests() {
    return new DirectChannel();
}

@Bean
public IntegrationFlow inboundFlow(ActiveMQConnectionFactory connectionFactory) {
    return IntegrationFlows
            .from(Jms.messageDrivenChannelAdapter(connectionFactory).destination("requests"))
            .channel(requests())
            .get();
}

/*
 * Configure outbound flow (replies going to the master)
 */
@Bean
public DirectChannel replies() {
    return new DirectChannel();
}

@Bean
public IntegrationFlow outboundFlow(ActiveMQConnectionFactory connectionFactory) {
    return IntegrationFlows
            .from(replies())
            .handle(Jms.outboundAdapter(connectionFactory).destination("replies"))
            .get();
}

/*
 * Configure the ChunkProcessorChunkHandler
 */
@Bean
@ServiceActivator(inputChannel = "requests", outputChannel = "replies")
public ChunkProcessorChunkHandler<Integer> chunkProcessorChunkHandler() {
    ChunkProcessor<Integer> chunkProcessor
            = new SimpleChunkProcessor<>(itemProcessor(), itemWriter());
    ChunkProcessorChunkHandler<Integer> chunkProcessorChunkHandler
            = new ChunkProcessorChunkHandler<>();
    chunkProcessorChunkHandler.setChunkProcessor(chunkProcessor);
    return chunkProcessorChunkHandler;
}

Most of these configuration items should look familiar from the master configuration. Workers do not need access to the Spring Batch JobRepository nor to the actual job configuration file. The main bean of interest is the chunkProcessorChunkHandler . The chunkProcessor property of ChunkProcessorChunkHandler takes a configured SimpleChunkProcessor , which is where you would provide a reference to your ItemWriter (and, optionally, your ItemProcessor ) that will run on the worker when it receives chunks from the master.

For more information, see the section of the "Scalability" chapter on Remote Chunking.

Starting from version 4.1, Spring Batch Integration introduces the @EnableBatchIntegration annotation that can be used to simplify a remote chunking setup. This annotation provides two beans that can be autowired in the application context:

  • RemoteChunkingMasterStepBuilderFactory : used to configure the master step

  • RemoteChunkingWorkerBuilder : used to configure the remote worker integration flow

These APIs take care of configuring a number of components as described in the following diagram:

Remote Chunking Configuration

Figure 4. Remote Chunking Configuration

On the master side, the RemoteChunkingMasterStepBuilderFactory allows you to configure a master step by declaring:

  • the item reader to read items and send them to workers

  • the output channel ("Outgoing requests") to send requests to workers

  • the input channel ("Incoming replies") to receive replies from workers

A ChunkMessageChannelItemWriter and the MessagingTemplate are not needed to be explicitly configured (Those can still be explicitly configured if required).

On the worker side, the RemoteChunkingWorkerBuilder allows you to configure a worker to:

  • listen to requests sent by the master on the input channel ("Incoming requests")

  • call the handleChunk method of ChunkProcessorChunkHandler for each request with the configured ItemProcessor and ItemWriter

  • send replies on the output channel ("Outgoing replies") to the master

There is no need to explicitly configure the SimpleChunkProcessor and the ChunkProcessorChunkHandler (Those can be explicitly configured if required).

The following example shows how to use these APIs:

@EnableBatchIntegration
@EnableBatchProcessing
public class RemoteChunkingJobConfiguration {

    @Configuration
    public static class MasterConfiguration {

        @Autowired
        private RemoteChunkingMasterStepBuilderFactory masterStepBuilderFactory;

        @Bean
        public TaskletStep masterStep() {
            return this.masterStepBuilderFactory.get("masterStep")
                       .chunk(100)
                       .reader(itemReader())
                       .outputChannel(requests()) // requests sent to workers
                       .inputChannel(replies())   // replies received from workers
                       .build();
        }

        // Middleware beans setup omitted

    }

    @Configuration
    public static class WorkerConfiguration {

        @Autowired
        private RemoteChunkingWorkerBuilder workerBuilder;

        @Bean
        public IntegrationFlow workerFlow() {
            return this.workerBuilder
                       .itemProcessor(itemProcessor())
                       .itemWriter(itemWriter())
                       .inputChannel(requests()) // requests received from the master
                       .outputChannel(replies()) // replies sent to the master
                       .build();
        }

        // Middleware beans setup omitted

    }

}

You can find a complete example of a remote chunking job here.

Remote Partitioning

Remote Partitioning

Figure 5. Remote Partitioning

Remote Partitioning, on the other hand, is useful when it is not the processing of items but rather the associated I/O that causes the bottleneck. Using Remote Partitioning, work can be farmed out to workers that execute complete Spring Batch steps. Thus, each worker has its own ItemReader , ItemProcessor , and ItemWriter . For this purpose, Spring Batch Integration provides the MessageChannelPartitionHandler .

This implementation of the PartitionHandler interface uses MessageChannel instances to send instructions to remote workers and receive their responses. This provides a nice abstraction from the transports (such as JMS and AMQP) being used to communicate with the remote workers.

The section of the "Scalability" chapter that addresses remote partitioning provides an overview of the concepts and components needed to configure remote partitioning and shows an example of using the default TaskExecutorPartitionHandler to partition in separate local threads of execution. For remote partitioning to multiple JVMs, two additional components are required:

  • A remoting fabric or grid environment

  • A PartitionHandler implementation that supports the desired remoting fabric or grid environment

Similar to remote chunking, JMS can be used as the "remoting fabric". In that case, use a MessageChannelPartitionHandler instance as the PartitionHandler implementation, as described above. The following example assumes an existing partitioned job and focuses on the MessageChannelPartitionHandler and JMS configuration:

XML Configuration

<bean id="partitionHandler"
   class="org.springframework.batch.integration.partition.MessageChannelPartitionHandler">
  <property name="stepName" value="step1"/>
  <property name="gridSize" value="3"/>
  <property name="replyChannel" ref="outbound-replies"/>
  <property name="messagingOperations">
    <bean class="org.springframework.integration.core.MessagingTemplate">
      <property name="defaultChannel" ref="outbound-requests"/>
      <property name="receiveTimeout" value="100000"/>
    </bean>
  </property>
</bean>

<int:channel id="outbound-requests"/>
<int-jms:outbound-channel-adapter destination="requestsQueue"
    channel="outbound-requests"/>

<int:channel id="inbound-requests"/>
<int-jms:message-driven-channel-adapter destination="requestsQueue"
    channel="inbound-requests"/>

<bean id="stepExecutionRequestHandler"
    class="org.springframework.batch.integration.partition.StepExecutionRequestHandler">
  <property name="jobExplorer" ref="jobExplorer"/>
  <property name="stepLocator" ref="stepLocator"/>
</bean>

<int:service-activator ref="stepExecutionRequestHandler" input-channel="inbound-requests"
    output-channel="outbound-staging"/>

<int:channel id="outbound-staging"/>
<int-jms:outbound-channel-adapter destination="stagingQueue"
    channel="outbound-staging"/>

<int:channel id="inbound-staging"/>
<int-jms:message-driven-channel-adapter destination="stagingQueue"
    channel="inbound-staging"/>

<int:aggregator ref="partitionHandler" input-channel="inbound-staging"
    output-channel="outbound-replies"/>

<int:channel id="outbound-replies">
  <int:queue/>
</int:channel>

<bean id="stepLocator"
    class="org.springframework.batch.integration.partition.BeanFactoryStepLocator" />

Java Configuration

/*
 * Configuration of the master side
 */
@Bean
public PartitionHandler partitionHandler() {
    MessageChannelPartitionHandler partitionHandler = new MessageChannelPartitionHandler();
    partitionHandler.setStepName("step1");
    partitionHandler.setGridSize(3);
    partitionHandler.setReplyChannel(outboundReplies());
    MessagingTemplate template = new MessagingTemplate();
    template.setDefaultChannel(outboundRequests());
    template.setReceiveTimeout(100000);
    partitionHandler.setMessagingOperations(template);
    return partitionHandler;
}

@Bean
public QueueChannel outboundReplies() {
    return new QueueChannel();
}

@Bean
public DirectChannel outboundRequests() {
    return new DirectChannel();
}

@Bean
public IntegrationFlow outboundJmsRequests() {
    return IntegrationFlows.from("outboundRequests")
            .handle(Jms.outboundGateway(connectionFactory())
                    .requestDestination("requestsQueue"))
            .get();
}

@Bean
@ServiceActivator(inputChannel = "inboundStaging")
public AggregatorFactoryBean partitioningMessageHandler() throws Exception {
    AggregatorFactoryBean aggregatorFactoryBean = new AggregatorFactoryBean();
    aggregatorFactoryBean.setProcessorBean(partitionHandler());
    aggregatorFactoryBean.setOutputChannel(outboundReplies());
    // configure other propeties of the aggregatorFactoryBean
    return aggregatorFactoryBean;
}

@Bean
public DirectChannel inboundStaging() {
    return new DirectChannel();
}

@Bean
public IntegrationFlow inboundJmsStaging() {
    return IntegrationFlows
            .from(Jms.messageDrivenChannelAdapter(connectionFactory())
                    .configureListenerContainer(c -> c.subscriptionDurable(false))
                    .destination("stagingQueue"))
            .channel(inboundStaging())
            .get();
}

/*
 * Configuration of the worker side
 */
@Bean
public StepExecutionRequestHandler stepExecutionRequestHandler() {
    StepExecutionRequestHandler stepExecutionRequestHandler = new StepExecutionRequestHandler();
    stepExecutionRequestHandler.setJobExplorer(jobExplorer);
    stepExecutionRequestHandler.setStepLocator(stepLocator());
    return stepExecutionRequestHandler;
}

@Bean
@ServiceActivator(inputChannel = "inboundRequests", outputChannel = "outboundStaging")
public StepExecutionRequestHandler serviceActivator() throws Exception {
    return stepExecutionRequestHandler();
}

@Bean
public DirectChannel inboundRequests() {
    return new DirectChannel();
}

public IntegrationFlow inboundJmsRequests() {
    return IntegrationFlows
            .from(Jms.messageDrivenChannelAdapter(connectionFactory())
                    .configureListenerContainer(c -> c.subscriptionDurable(false))
                    .destination("requestsQueue"))
            .channel(inboundRequests())
            .get();
}

@Bean
public DirectChannel outboundStaging() {
    return new DirectChannel();
}

@Bean
public IntegrationFlow outboundJmsStaging() {
    return IntegrationFlows.from("outboundStaging")
            .handle(Jms.outboundGateway(connectionFactory())
                    .requestDestination("stagingQueue"))
            .get();
}

You must also ensure that the partition handler attribute maps to the partitionHandler bean, as shown in the following example:

XML Configuration

<job id="personJob">
  <step id="step1.master">
    <partition partitioner="partitioner" handler="partitionHandler"/>
    ...
  </step>
</job>

Java Configuration

public Job personJob() {
                return jobBuilderFactory.get("personJob")
                                .start(stepBuilderFactory.get("step1.master")
                                                .partitioner("step1.worker", partitioner())
                                                .partitionHandler(partitionHandler())
                                                .build())
                                .build();
        }

You can find a complete example of a remote partitioning job here.

The @EnableBatchIntegration annotation that can be used to simplify a remote partitioning setup. This annotation provides two beans useful for remote partitioning:

  • RemotePartitioningMasterStepBuilderFactory : used to configure the master step

  • RemotePartitioningWorkerStepBuilderFactory : used to configure the worker step

These APIs take care of configuring a number of components as described in the following diagram:

Remote Partitioning Configuration (with job repository polling)

Figure 6. Remote Partitioning Configuration (with job repository polling)

Remote Partitioning Configuration (with replies aggregation)

Figure 7. Remote Partitioning Configuration (with replies aggregation)

On the master side, the RemotePartitioningMasterStepBuilderFactory allows you to configure a master step by declaring:

  • the Partitioner used to partition data

  • the output channel ("Outgoing requests") to send requests to workers

  • the input channel ("Incoming replies") to receive replies from workers (when configuring replies aggregation)

  • the poll interval and timeout parameters (when configuring job repository polling)

The MessageChannelPartitionHandler and the MessagingTemplate are not needed to be explicitly configured (Those can still be explicitly configured if required).

On the worker side, the RemotePartitioningWorkerStepBuilderFactory allows you to configure a worker to:

  • listen to requests sent by the master on the input channel ("Incoming requests")

  • call the handle method of StepExecutionRequestHandler for each request

  • send replies on the output channel ("Outgoing replies") to the master

There is no need to explicitly configure the StepExecutionRequestHandler (which can be explicitly configured if required).

The following example shows how to use these APIs:

@Configuration
@EnableBatchProcessing
@EnableBatchIntegration
public class RemotePartitioningJobConfiguration {

    @Configuration
    public static class MasterConfiguration {

        @Autowired
        private RemotePartitioningMasterStepBuilderFactory masterStepBuilderFactory;

        @Bean
        public Step masterStep() {
                 return this.masterStepBuilderFactory
                    .get("masterStep")
                    .partitioner("workerStep", partitioner())
                    .gridSize(10)
                    .outputChannel(outgoingRequestsToWorkers())
                    .inputChannel(incomingRepliesFromWorkers())
                    .build();
        }

        // Middleware beans setup omitted

    }

    @Configuration
    public static class WorkerConfiguration {

        @Autowired
        private RemotePartitioningWorkerStepBuilderFactory workerStepBuilderFactory;

        @Bean
        public Step workerStep() {
                 return this.workerStepBuilderFactory
                    .get("workerStep")
                    .inputChannel(incomingRequestsFromMaster())
                    .outputChannel(outgoingRepliesToMaster())
                    .chunk(100)
                    .reader(itemReader())
                    .processor(itemProcessor())
                    .writer(itemWriter())
                    .build();
        }

        // Middleware beans setup omitted

    }

}